軟銀牽頭向Zymergen投資1.3億美元
SoftBank has led a $130m investment in a US bioengineering startup that makes “designer microbes”, in the latest sign of artificial intelligence and robotics invading the natural sciences.
軟銀(SoftBank)牽頭向美國一家生產“設計師微生物”的生物工程創業型公司投資1.3億美元，這是人工智能和機器人進軍自然科學的最新跡象。
The three-year-old venture, Zymergen, uses machine learning and other techniques to re-engineer the genetic make-up of micro-organisms. The enhanced microbes are used in existing industrial processes including making generic pharmaceuticals, but its backers hope the technology will also open the way to bigger breakthroughs.
創立三年的Zymergen利用機器學習等技術重新設計微生物的基因構成。得到強化的微生物正用於包括生產仿製藥在內的現有工業流程，但Zymergen的投資者希望，這項技術還能開闢出取得更大突破的道路。
Deep Nishar, head of the SoftBank’s new investments group, said the gene-editing of microbes could eventually be used to create new materials, such as adhesives that work in extreme conditions or flexible electronics for consumer gadgets that wouldn’t break when dropped.
軟銀新成立的投資集團的負責人迪普•尼沙爾(Deep Nishar)表示，微生物基因編輯最終可用於創造新材料，比如工作於極端條件下的粘合劑或柔性電子器件，後者可用來生產掉落後不會破碎的消費類電子產品。
Zymergen is part of a new generation of companies trying to use advanced computing to enhance bioengineering.
Zymergen是新一代試圖利用先進計算來增強生物工程的企業之一。
Steven Chu, a former US energy secretary and Nobel prizewinner who is joining the Zymergen board, said that re-engineering the genomes of microbes had so far proved more difficult than anticipated, despite their relatively simple composition.
前美國能源部長、諾貝爾獎得主朱棣文(Steven Chu)也將加入Zymergen董事會。他表示，迄今爲止的事實證明，重新設計微生物基因組比預期的要難，儘管它們的構成相對簡單。
“You have to find a better way to programme the gene set,” Mr Chu said. He described the type of computing used by Zymergen as “the beginning of a new type of chemistry”.
朱棣文說：“你必須找到更好的方法來編輯基因組。”他說，Zymergen採用的那種計算“開啓了一種新型的化學”。
The company uses machine learning — a form of advanced pattern recognition — to try to identify the groups of genes inside microbes that are likely to cause a desired result, such as producing a certain protein. That is designed to replace current approaches largely based on trial and error and could yield far more efficient organisms.
Zymergen使用機器學習（一種先進的模式識別）來試圖找出微生物內部可能導致所需結果的基因組，比如能產生某種蛋白質的基因組。該方法旨在取代目前主要基於試錯的方法，有可能生成有效得多的微生物。
